Scientist – Digital Discovery: Biological Data Systems & Machine Learning

Amgen•Burnaby, BC

About The Position

Join Amgen’s Mission of Serving Patients. At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Scientist – Digital Discovery: Biological Data Systems & Machine Learning. What you will do. Let’s do this. Let’s change the world. In this vital role, we are seeking a Scientist, Biological Data Systems & Machine Learning to join the Digital Discovery team. This role sits at the intersection of wet-lab experimental biology, data systems, and machine learning, enabling a closed-loop discovery engine where data generation, structuring, and modeling continuously inform one another.

Requirements

PhD in Biology, Immunology, Immunoengineering, Biochemistry, Bioengineering or related field OR Master’s degree + 3+ years of relevant experience OR Bachelor’s degree + 5+ years of relevant experience

Nice To Haves

Training in Bioinformatics, or related field
Strong background in wet-lab biology
Experience with large-scale biological datasets
Experience with data modeling, curation, and ETL pipelines
Proficiency in Python and/or R
Experience with machine learning approaches
Familiarity with scientific data platforms (e.g., Benchling)
Experience working cross-functionally across science, data, and engineering teams

Responsibilities

Define and implement data models, schemas, and relationships for biological data
Ensure robust data lineage, metadata standards, and interoperability across systems
Establish best practices for ML-ready biological datasets
Identify, access, and harmonize proprietary legacy discovery datasets
Perform data archaeology to reconstruct experimental context and metadata
Build high-quality, ML-ready training datasets for model development
Partner with AI/ML teams on data requirements and dataset design
Translate experimental workflows into digital systems (e.g., Benchling)
Define requirements for workflows, entities, and dashboards with engineering teams
Ensure data is captured in a structured, future-ready manner
Analyze large-scale biological datasets to generate insights
Support development of predictive and generative ML models
Optimize dataset structure and feature engineering
Interface across experimental biology, AI/ML, data engineering, and business teams
Translate scientific needs into technical requirements and vice versa
Align workflows with enterprise data ecosystem strategies
Identify inefficiencies and design scalable data workflows
Develop tools and dashboards to improve data accessibility and usability
Ensure robustness and integrity of datasets and tools
Identify edge cases and prevent downstream issues
Drive adoption of data platforms and best practices
Serve as a trusted advisor to scientists on data standards and workflows